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Hadoop Developer In Real World

Big Data In Real World

4.7

Based on 3,467 ratings

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Big Data In Real World

From the creators of the successful Hadoop Starter Kit course hosted in Udemy, comes Hadoop In Real World course. This course is designed for anyone who aspire a career as a Hadoop developer. In this course we have covered all the concepts that every aspiring Hadoop developer must know to SURVIVE in

The course covers all the must know topics like HDFS, MapReduce, YARN, Apache Pig and Hive etc. and we go deep in exploring the concepts. We just don’t stop with the easy concepts, we take it a step further and cover important and complex topics like file formats, custom Writables, input/output formats, troubleshooting, optimizations etc.

All concepts are backed by interesting hands-on projects like analyzing million song dataset to find less familiar artists with hot songs, ranking pages with page dumps from wikipedia, simulating mutual friends functionality in Facebook just to name a few.

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What's inside

Learning objectives

Understand what is big data, the challenges with big data and how hadoop propose a solution for the big data problem
Work and navigate hadoop cluster with ease
Install and configure a hadoop cluster on cloud services like amazon web services (aws)
Understand the difference phases of mapreduce in detail
Write optimized pig latin instruction to perform complex data analysis
Write optimized hive queries to perform data analysis on simple and nested datasets
Work with file formats like sequencefile, avro etc

Understand hadoop architecture, single point of failures (spof), secondary/checkpoint/backup nodes, ha configuration and yarn
Tune and optimize slowing running mapreduce jobs, pig instructions and hive queries
Understand how joins work behind the scenes and will be able to write optimized join statements
Wherever possible, students will be introduced to difficult questions that are asked in real hadoop interviews
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Understand what is big data, the challenges with big data and how hadoop propose a solution for the big data problem
Work and navigate hadoop cluster with ease
Install and configure a hadoop cluster on cloud services like amazon web services (aws)
Understand the difference phases of mapreduce in detail
Write optimized pig latin instruction to perform complex data analysis
Write optimized hive queries to perform data analysis on simple and nested datasets
Work with file formats like sequencefile, avro etc
Understand hadoop architecture, single point of failures (spof), secondary/checkpoint/backup nodes, ha configuration and yarn
Tune and optimize slowing running mapreduce jobs, pig instructions and hive queries
Understand how joins work behind the scenes and will be able to write optimized join statements
Wherever possible, students will be introduced to difficult questions that are asked in real hadoop interviews
Show more
Show less

Syllabus

In this section, we will learn about the course structure and the prerequisites for the course. We will help you setup all the necessary things needed to proceed with the course.

With Amazon EMR we can start a brand new Hadoop cluster and run MapReduce jobs in matter of minutes. This lecture will walk through step by step how to set up a Hadoop cluster and run MapReduce jobs in it.

In this lecture we will learn about the benefits of Cloudera Manager, differences between Packages and Parcels and lifecycle of Parcels.

In this lecture we will see how to install a 3 node Hadoop cluster on AWS using Cloudera Manager

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Read about what's good

what should give you pause

and possible dealbreakers

Covers several facets of Big Data, introducing learners to multiple core pieces of the Big Data ecosystem, including HDFS, MapReduce, Apache Pig, and Apache Hive

Teaches complex topics in depth, going beyond simple, easy-to-understand concepts

Provides relevant introduction to Big Data for those looking to begin their career as Hadoop developers

Offers hands-on practice through projects focused on real-world tasks, such as analyzing large datasets to identify underrepresented artists with popular songs

Introduces learners to Hadoop, a widely used framework for processing and managing Big Data

Covers core concepts like HDFS, MapReduce, Apache Pig, and Hive, essential for aspiring Hadoop developers

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Reviews summary

Practical hadoop development with real-world projects

According to students, this course is a highly practical and comprehensive guide for aspiring Hadoop developers, emphasizing real-world applications and interview readiness. Learners particularly praise the insightful hands-on projects, which effectively solidify understanding of complex topics like Pig and Hive. The instructor's explanations are frequently noted as clear and concise, making advanced concepts accessible. However, a significant number of learners report difficulties with the initial setup process, citing outdated instructions that often require external research. Some also feel the pace can be fast for complete beginners and suggest older sections could benefit from updates, but overall, it provides a strong foundation for a Big Data career.

Instructor provides clear and concise explanations.

"The instructor's explanations were clear and concise, making complex topics easy to grasp."

"The instructor explains complex concepts simply, and the practical examples are spot on."

"The explanations are very clear, and the hands-on projects are excellent."

Covers essential and advanced Hadoop concepts thoroughly.

"This course is exceptionally well-structured and highly practical for anyone looking to become a Hadoop developer."

"The coverage of different file formats like SequenceFile and AVRO was comprehensive and much needed."

"It's truly comprehensive, covering everything from basic HDFS to advanced optimizations and cluster setup on AWS."

"I appreciated the depth the course goes into, especially with MapReduce and Hive queries."

Excellent preparation for Hadoop developer roles, including interview insights.

"It truly prepares you for a career in Big Data."

"The 'real world' aspect is definitely there with the interview questions and optimization tips."

"The insights into interview questions and performance tuning are invaluable. Highly recommended for aspiring Hadoop developers."

Reinforces concepts with engaging, real-world scenarios.

"The hands-on projects, especially the Million Song Dataset analysis and Page Ranking, were incredibly insightful and helped solidify my understanding of Pig and Hive."

"I found the practical exercises on Twitter data analysis with Hive particularly engaging."

"The projects are the strong point, they truly make you apply what you learn."

May be too fast for complete beginners without prior experience.

"I felt like the pace was a bit too fast for a complete beginner in some sections."

"I'd recommend it for those with some prior programming experience."

"I think some of the core concepts could be explained more clearly, especially for someone new to distributed systems."

Initial environment setup can be difficult and outdated.

"I struggled with the setup instructions on Windows. It took a lot of time to get the environment running, and I needed to consult online forums frequently."

"The setup process was a nightmare. I spent more time trying to get the environment to work than actually learning."

"For a beginner, the initial setup can be daunting, but persistence pays off."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Hadoop Developer In Real World with these activities:

Attend a Hadoop Meetup

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Connect with other Hadoop professionals.

Browse courses on Hadoop

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Find a Hadoop Meetup in your area.
Attend the Meetup.
Network with other attendees.

Follow a Hadoop tutorial series

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Build a strong foundation in Hadoop.

Browse courses on Hadoop

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Find a Hadoop tutorial series.
Follow the tutorial series.
Complete the assignments.

Review 'Hadoop: The Definitive Guide' by Tom White

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Review the concepts covered in the course.

View Hadoop: The Definitive Guide: Storage and... on Amazon

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Read the first three chapters of the book.
Summarize the key concepts covered in each chapter.
Identify any areas where you need further clarification.

Six other activities

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Show all nine activities

Attend a Hadoop workshop

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Gain hands-on experience with Hadoop.

Browse courses on Hadoop

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Find a Hadoop workshop in your area.
Attend the workshop.
Complete the exercises.

Create a Hadoop cluster on AWS

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Gain hands-on experience with Hadoop.

Browse courses on Hadoop

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Sign up for an AWS account.
Launch an EC2 instance.
Install Hadoop on the EC2 instance.
Configure Hadoop.
Run a Hadoop job.

Practice MapReduce programming

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Develop proficiency in MapReduce programming.

Browse courses on Hadoop

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Find a MapReduce programming tutorial.
Complete the tutorial.
Practice writing MapReduce programs.

Write a blog post about Hadoop

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Deepen your understanding of Hadoop by explaining it to others.

Browse courses on Hadoop

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Choose a topic related to Hadoop.
Research the topic.
Write a blog post about the topic.
Publish the blog post.

Contribute to the Hadoop open source project

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Gain experience with open source development and contribute to the Hadoop community.

Browse courses on Hadoop

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Find a Hadoop open source project.
Review the project documentation.
Make a contribution to the project.

Develop a data analytics application using Hadoop

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Apply your Hadoop skills to solve a real-world problem.

Browse courses on Hadoop

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Identify a problem that can be solved using Hadoop.
Design a data analytics application.
Develop the application.
Test the application.
Deploy the application.

Career center

Learners who complete Hadoop Developer In Real World will develop knowledge and skills that may be useful to these careers:

Hadoop Developer

Hadoop Developers work with Big Data, and this course will be the perfect way to get started in this in-demand career. Graduates of this course will have the skills needed to succeed in this role and help contribute to organizational success.

See salaries and explore the career path for Hadoop Developer

Data Analyst

Data Analysts help businesses discover patterns in data to make better decisions. With its focus on analyzing large datasets using MapReduce, Pig, and Hive, this course can serve as a helpful stepping stone for a career in this field.

See salaries and explore the career path for Data Analyst

Big Data Architect

Big Data Architects design and oversee the deployment of data-related systems. The knowledge of HDFS, Hadoop architecture, and YARN taught in this course will be key to understanding this field and designing effective architecture for Big Data environments.

See salaries and explore the career path for Big Data Architect

Data Engineer

Data Engineers create and maintain data pipelines to ensure the integrity and quality of data in an organization. This course's coverage of HDFS, MapReduce, and YARN will provide a helpful foundation for a successful career in this role.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers can work in a variety of domains, including Big Data. This course will help those with an interest in the latter build foundational knowledge of Hadoop ecosystem tools like HDFS, MapReduce, Pig, and Hive.

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Cloud Engineer

Cloud Engineers manage the deployment and operation of cloud-based systems, and part of this role may include working with Big Data technologies like Hadoop. This course's coverage of Amazon Web Services will be particularly helpful for those who plan to specialize in cloud-based Big Data solutions.

See salaries and explore the career path for Cloud Engineer

Data Scientist

Data Scientists use scientific methods to extract knowledge from data. While this course does not cover all topics necessary for a career in this field, the focus on analyzing large datasets using MapReduce, Pig, and Hive is a useful starting point.

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Database Administrator

Database Administrators ensure the efficient operation of database systems. This course will provide an introduction to HDFS, a distributed file system used to store Big Data. While not all Database Administrators work with Big Data, this knowledge will be useful for those who do.

See salaries and explore the career path for Database Administrator

Business Analyst

Business Analysts help businesses make informed decisions by analyzing data. This course covers how to analyze large datasets using MapReduce, Pig, and Hive, which will be in-demand skills for Business Analysts working in data-intensive industries.

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Statistician

Statisticians collect and analyze data to provide insights and support decision-making. This course's focus on analyzing large datasets using MapReduce, Pig, and Hive is highly relevant to Statisticians who want to work with Big Data.

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Operations Research Analyst

Operations Research Analysts use mathematical models to optimize operations and decision-making. This course will help build a foundation for understanding and working with Big Data, which is increasingly being used for operations research.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts develop and use mathematical models to analyze financial data. This course will provide an introduction to HDFS, a distributed file system used to store Big Data, which will be useful for those who want to work with Big Data in the financial industry.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models to solve business problems. While this course does not cover all topics necessary for this role, the focus on analyzing large datasets using MapReduce, Pig, and Hive will be helpful for those who want to specialize in Big Data machine learning.

See salaries and explore the career path for Machine Learning Engineer

Data Warehouse Developer

Data Warehouse Developers design and build data warehouses to store and manage large amounts of data. This course's focus on HDFS, MapReduce, Pig, and Hive will be useful for those who want to specialize in Big Data data warehousing.

See salaries and explore the career path for Data Warehouse Developer

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Hadoop Developer In Real World.

Hadoop: The Definitive Guide

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Provides comprehensive coverage of Hadoop, including its architecture, components, and use cases. It valuable reference for those looking to gain a deeper understanding of Hadoop.

Hadoop Developer In Real World

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Practical hadoop development with real-world projects

Activities

Career center

Reading list

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